Johannes Kepler University Linz
1 month ago
PhD Position: Data-Assisted Real-Time Simulations of Particulate Flows Johannes Kepler University Linz (JKU) in Austria
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Austria
University
Johannes Kepler University Linz

How do Korean students apply for this?
Sign in for free to reveal details, requirements, and source links.
Where to contact
Keywords
About this position
This fully funded PhD position at Johannes Kepler University Linz (JKU), Austria, offers an exciting opportunity to conduct research in data-assisted computational modeling of particulate multiscale and multiphysics flows. The project is embedded within the newly established Christian Doppler Laboratory for Data-Assisted Simulations of Complex Flows and is carried out in close collaboration with the industrial partner Plansee SE, Reutte, Austria. The successful candidate will spend 6–8 weeks per year on-site at Plansee SE, gaining valuable industry experience and contributing to real-world applications.
The research will focus on developing surrogate models, such as recurrence CFD, for real-time simulations and contributing to digital process twins for industrial furnaces. The project aims to address fundamental questions in data-assisted modeling, with the broader goal of reducing energy consumption and CO₂ emissions in industrial processes. The candidate will collaborate within a dynamic research group and benefit from access to high-performance computing resources, international collaborations, and opportunities for conference participation and career development.
Applicants should have a Master’s degree in Physics, Applied Mathematics, Mechanical Engineering, Computational Science, or a related field. A strong background in classical simulation techniques (e.g., CFD, CFD-DEM) and proficiency in at least one scientific computing language are required. Interest in or willingness to learn deep learning or other data-driven modeling methods is expected. Experience with machine learning frameworks, physics-based simulations, and experimental validation is advantageous. The position requires willingness to conduct on-site visits and interact with industrial partners; German language skills are desirable but not mandatory.
The position offers full funding, with employment at JKU and a gross salary of EUR 3,715 per month (paid 14 times per year). The anticipated start date is January 2026 or as soon as possible thereafter. To apply, candidates should submit a cover letter detailing their research interests and motivation, along with a 2-page CV (including relevant publications, if any) to [email protected] or apply via the provided application link.
Funding details
Available
What's required
Applicants must hold a Master’s degree in Physics, Applied Mathematics, Mechanical Engineering, Computational Science, or a related field. A solid background in classical simulation techniques such as CFD or CFD-DEM and strong programming skills in at least one scientific computing language are required. Interest in or willingness to learn deep learning or other data-driven modeling methods is expected. Experience with machine learning frameworks, physics-based simulations, and experimental skills for validation experiments are beneficial. Willingness to conduct on-site visits and interact with industrial partners is necessary. German language skills are desirable but not mandatory.
How to apply
Send your application documents, including a cover letter and a 2-page CV, to [email protected] or apply directly via the provided application link. Ensure your cover letter details your research interests and motivation. Include any relevant publications in your CV.
Ask ApplyKite AI

How do Korean students apply for this?
Sign in for free to reveal details, requirements, and source links.